Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Explanation in Bayesian belief networks
Explanation in Bayesian belief networks
Probabilistic reasoning in decision support systems: from computation to common sense
Probabilistic reasoning in decision support systems: from computation to common sense
Introduction to Bayesian Networks
Introduction to Bayesian Networks
Qualtitative propagation and scenario-based scheme for exploiting probabilistic reasoning
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Generating Explanations Based on Markov Decision Processes
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
Compact explanation of data fusion decisions
Proceedings of the 22nd international conference on World Wide Web
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Bayesian networks have proved to be an appropriate tool for medical diagnosis, because uncertain reasoning in this field is based on a combination of causal knowledge and statistical data. However, a condition for the acceptance of a medical expert system is the ability to explain the diagnosis. This is a difficult task, because probabilistic inference seems to have little relation with human thinking. The current paper focuses on the graphic interface that constitutes one of the explanation capabilities of Elvira, a software tool for the edition and evaluation of graphical probabilistic models. The method we describe consists in working with different evidence cases and simultaneously displaying the corresponding probabilities.